Big Data: Understanding How Data Powers Big Business

This document was uploaded by one of our users. The uploader already confirmed that they had the permission to publish it. If you are author/publisher or own the copyright of this documents, please report to us by using this DMCA report form.

Simply click on the Download Book button.

Yes, Book downloads on Ebookily are 100% Free.

Sometimes the book is free on Amazon As well, so go ahead and hit "Search on Amazon"

Leverage big data to add value to your business

Social media analytics, web-tracking, and other technologies help companies acquire and handle massive amounts of data to better understand their customers, products, competition, and markets. Armed with the insights from big data, companies can improve customer experience and products, add value, and increase return on investment. The tricky part for busy IT professionals and executives is how to get this done, and that's where this practical book comes in. Big Data: Understanding How Data Powers Big Business is a complete how-to guide to leveraging big data to drive business value.

Full of practical techniques, real-world examples, and hands-on exercises, this book explores the technologies involved, as well as how to find areas of the organization that can take full advantage of big data.

  • Shows how to decompose current business strategies in order to link big data initiatives to the organization’s value creation processes
  • Explores different value creation processes and models
  • Explains issues surrounding operationalizing big data, including organizational structures, education challenges, and new big data-related roles
  • Provides methodology worksheets and exercises so readers can apply techniques
  • Includes real-world examples from a variety of organizations leveraging big data

Big Data: Understanding How Data Powers Big Business is written by one of Big Data's preeminent experts, William Schmarzo. Don't miss his invaluable insights and advice.

Author(s): Bill Schmarzo
Publisher: Wiley
Year: 2013

Language: English
Pages: 240
Tags: Информатика и вычислительная техника;Искусственный интеллект;Интеллектуальный анализ данных;